Population-adaptive differential evolution-based power allocation algorithm for cognitive radio networks

被引:0
作者
Xiu Zhang
Xin Zhang
机构
[1] Tianjin Normal University,College of Electronic and Communication Engineering
[2] Tianjin Normal University,Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission
来源
EURASIP Journal on Wireless Communications and Networking | / 2016卷
关键词
Cognitive radio networks; Differential evolution; Power allocation; Resource allocation; Parameter control;
D O I
暂无
中图分类号
学科分类号
摘要
Cognitive radio (CR) networks have drawn great attention in wireless communication fields. Efficient and reliable communication is a must to provide good services and assure a high-quality life for human beings. Resource allocation is one of the key problems in information transmission of CR networks. This paper studies power allocation in cognitive multiple input and multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Power allocation is modeled as a minimization problem with three practical constraints. To deal with the problem, a population-adaptive differential evolution (PADE) algorithm is proposed. All algorithmic parameters are adaptively controlled in PADE. In numerical experiment, three test cases are simulated to study the performance of the proposed algorithm. Particle swarm optimization, differential evolution (DE), an adaptive DE, and artificial bee colony algorithms are taken as baseline. The results show that PADE presents the best performance among all test algorithms over all test cases. The proposed PADE algorithm can also be used to tackle other resource allocation problems.
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